EFFECTIVENESS EVALUATION
OF OPERATOR TRAINING
CONDUCTED UNDER THE
PSC PROGRAM
>^fcn si?r A
Revised March 1973
U.S. ENVIRONMENTAL PROTECTION AGENCY
Washington, D.C. 20460
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ACKNOWLEDGMENTS
The Environmental Protection Agency and Harbridge House
wishes to acknowledge and thank the Texas Water Quality
Board's Environmental Education Program, the Texas State
Department of Health's Division of Sanitary Engineering, and
the North Central Texas Council of Governments for their
contributions and cooperation in making this publication
possible.
This report addresses only one of the many training programs
currently underway in the State of Texas. Recognition should
be given to the cities of the State for their outstanding record
of training in the field of water quality control. In conducting
and evaluating operator training in the Public Service Careers
Program, it was determined that Texas, due to its comprehen-
sive training efforts, would provide an excellent basis for con-
ducting this study.
Despite the generous assistance of the organizations mentioned,
the findings, conclusions and recommendations presented in
this report remain the responsibility of Harbridge House.
For additional copies, contact:
State & Local Manpower Development Branch
Manpower Development Staff
Environmental Protection Agency
Washington, D. C. 20460
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EFFECTIVENESS EVALUATION OF
OPERATOR TRAINING CONDUCTED UNDER
THE PSC PROGRAM
by
J. Craig McLanahan
and
R. Clark Tefft
for the
Public Service Careers Section
State & Local Manpower Development Branch
Manpower Development Staff
Environmental Protection Agency
15 June 1972
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EPA REVIEW NOTICE
This report has been reviewed by the Environmental Protection
Agency and approved for publication. Approval does not signify that
the contents necessarily reflect the views and policies of the
Environmental Protection Agency, nor does mention of trade names
or commercial products constitute endorsement or recommendation
for use.
(ii)
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ABSTRACT
The relationship between wastewater treatment plant operator
training and plant performance in Texas was studied using three
different approaches:
(i) An analysis of the performance of a sample of plants
involved in Operation Cleansweep, a Texas Water
Quality Board (WQB) project to clean up the poorest
performing plants in the state.
(ii) A survey of WQB field supervisors and their staffs to
determine which plants had improved as a result of
training and why that improvement had taken place.
(iii) A statistical correlation of operator training com-
pleted and level of plant performance for a sample of
124 plants.
Plant performance was found to be greatly influenced by training in
all of these studies, and this influence was found to be powerful
enough to cause some plants to change from a seriously noncom-
pliant status to a fully compliant performance substantially as a
result of training.
Once the magnitude of the performance change was calculated, a
monetary value for the change was estimated using the concept that
the relative cleanliness of the plant effluent was a measure of plant
productivity which could be converted into a "return" on capital
invested in the facility. Accordingly, poor plant performance gave
very low returns, and the improved performance due to operator
training yielded very high returns estimated at $91 of incremental
asset value for each dollar invested in training.
Other values derived in this study include a high investment in plant
per operator, over $64,000, a figure approximately six times the
average industrial investment per production worker.
(iii)
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TABLE OF CONTENTS
Page
I. Conclusions 1
II. Recommendations 3
III. Introduction 5
A. Purpose and Scope 5
B. Research Methodology 6
IV. The Impact of Operator Training on
Wastewater Treatment Plant Performance 11
: i
A. The Impact of Training in Improving
Wastewater Treatment Plant Performance 11
B. The Impact of Training in Sustaining
High Wastewater Treatment Plant
Performance 32
C. Conclusions Regarding the Impact of
Operator Training on Plant Performance 46
V. The Return on the Public Investment in
Wastewater Treatment Plant Operator
Training 51
A. Value of Capital Assets per Operator 51
B. Wasted Investment Through Substandard
Effluent 58
C. Conclusions Regarding the Return on the
Public Investment in Wastewater Treat-
ment Plant Operator Training 64
APPENDIX A ECI per Operator Calculations
for 19 Case Studies 65
ACKNOWLEDGMENTS 67
(iv)
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LIST OF EXHIBITS
Page
Exhibit 1 Summary of Operation Cleansweep
Case Analysis 17
Exhibit 2 Summary of WQB Supervisor Survey
Case Analysis 29
Exhibit 3 Typical Plant Entry in WQB Self-
Monitoring Computer Reports 33
Exhibit 4* Operator Certification Requirements
in Texas 35
Exhibit 5 Sample Computerized Correlation
Matrix 38
Exhibit 6 INT:PER Correlations 39
Exhibit 7 TA:PER Correlations 40
Exhibit 8 TfliPER Correlations 43
Exhibit 9 TcPER Correlations 44
Exhibit 10 Relative Correlation Frequencies of
TA> TB, and TC Factors with
Performance 45
Exhibit 11 Correlation of Changes in Plant
Performance with Training and
Staffing Parameters 47
Exhibit 12 Relative Values of Correlations of
Changes in Plant Performance with
Training and Staffing Parameters 48
Exhibit 13 Calculated Capital Investment per
Operator for 50 Randomly
Selected Plants 53
Exhibit 14 Summary of Black and Veatch
Plant Type Categories 55
(v)
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Page
Exhibit 15 Per Capita Wastewater Treatment
Plant Investment Cost Data 57
Exhibit 16 Calculation of "Stop-Loss" on
Capital Investment and Return on
Training Investment in 19 Case
Studies 60
(vi)
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PARTI
CONCLUSIONS
Three independent investigatory tracks have produced com-
plementary results which, when taken together, prove beyond
reasonable doubt that the Public Service Careers Program type
of training of municipal wastewater treatment plant operators
improves skills and increases plant effectiveness. However, in
specific cases the use of trained operators alone may be
ineffective in promoting good plant performance. The avail-
ability of adequately trained personnel alone does not ensure
effective operation; however, their unavailability ensures in-
effective operation.
Use of untrained or inadequately trained operators exposes the
public to a loss of the benefits from a productive public asset, in
effect decreasing the return on capital invested in treatment
plants. While this loss is difficult or impossible to assess
precisely, certain useful, if imperfect, estimates have been made.
(i) Risk of capital dissipation is substantial if untrained or
inadequately trained operators are utilized. Based on Texas
data, a conservative estimate of average plant value
entrusted to each operator is approximately $64,000.
Because of understaffing, individual operators are actually
entrusted with capital plant of up to $160,000.
(ii) In 19 Texas plants where training during 1971 has been
identified as the substantial cause of improved plant
performance, it is estimated that almost $5 million in
capital dissipation has been avoided through training. The
cost of training in all of these plants, at maximum
estimate, was $62,715. The estimated return on each
dollar invested in training in these plants in terms of
capital stop-loss is $91.
(iii) Other substantial but unmeasurable returns from training
in many of the other 1,000 or so Texas plants have
undoubtedly occurred. Returns from these plants plus the
19 above may be contrasted with the $690,000 in federal
investment in operator training in Texas between January
1969 and December 1971.
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(iv) In 19 Texas plants, BOD/TSS performance has improved
in a range of 112 percent to 334 percent as substantial
result of the operator training.
Training probably increases the cost of operations and routine
maintenance which are funded out of local funds. Therefore, by
itself, training may not be an appealing investment to local
decision-makers. However, in Texas, and in other states which
provide heavy fines for noncompliant plant operation, training
which moves a plant to compliance will provide a substantial
stop-loss return to a locality.
Prior to the conduct of this study, the Harbridge House project
team had anticipated that operator training did have a positive
effect on plant performance. However, the measurable value of
such training in terms of the return on investment in that
training astounded us.
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PART II
RECOMMENDATIONS
This study shows the salutary effect of operator training on
treatment plant effectiveness in Texas. Further, with regard to a
sample of 19 established Texas plants, it indicates an extremely high
return on training investment in terms of halting dissipation of
capital invested in plant and in other unmeasured ways. It also shows
a high plant investment per operator and thus displays the substantial
risk in entrusting plant to untrained or unlicensed operators. We see
no reason why the Texas findings for established plants are not valid
for the rest of the United States; the extent of the return on the
training dollar may vary, but even a substantially smaller return than
shown in Texas remains a very excellent investment. Therefore, we
recommend that EPA proceed as rapidly as possible to develop and
implement programs designed to ensure training and certification for
plant operators.
Anticipated federal and state capital investment in new plants during
the next five years is in the billions. We can speculate that the
relationship of trained operators to plant effectiveness for new plants
coming on line will be similar to that for established plants as
determined in this study. However, this is speculation. We recom-
mend that further research and analyses be undertaken to establish
the effect of operator training on new plant effectiveness and the
return on investment in training operators for these plants.
In anticipation of a finding from such research and analyses that
operator training does have the result of preventing substantial
capital dissipation in new plants, we recommend that EPA take the
necessary legal and administrative steps necessary to be immediately
ready to make operator training and certification a condition of
plant construction grants. Rapid implementation action would be
prudent in order to prevent wasting of federal capital investment.
EPA should note that a requirement for training will create a demand
for training. The EPA current estimate for additional operators is
43,600 in the next five years. (This is in addition to upgrade training
demands for existing operators necessary to protect the present
investment in plant.) This additional demand to man the new plants
underscores our previous recommendation that EPA press forward
with programs designed to ensure training and certification for
operators.
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The report notes that available evidence suggests that routine plant
operation and maintenance costs increase with the use of trained
operators. Since these costs are born by the localities which are
generally financially hard pressed, there is likely a disincentive for
localities to encourage operator training. Some states, such as Texas,
have a procedure for fining localities with plants not meeting
specified performance requirements. Such a fine system provides an
incentive for localities to see to operator training. We recommend
that EPA encourage the states to adopt and/or enforce a fine system
or some other mechanism which provides an incentive to localities to
train and certify all operators.
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PART m
INTRODUCTION
A. Purpose and Scope
This report presents the results of a study conducted for the
Environmental Protection Agency (EPA) regarding the effectiveness
and return on investment of wastewater treatment plant operator
training particularly that supported by federal funds through the
Public Service Careers (PSC) and similar programs. Because of the
similarity of operator training conducted under the sponsorship or
influence of EPA in terms of work skills developed and substantive
content, PSC program results can reasonably be imputed to other
programs, and vice versa.
The effectiveness of wastewater treatment plant operator training
programs in increasing the applied skills of their graduates the first
major area of investigation can most appropriately be measured in
terms of quality of plant output or effluent. This study examines the
impact of training on plant performance in two ways: (i) the ability
of training to improve plant performance by changing operator skills
and behavior, and (ii) the influence of training in maintaining
consistently high performance at already successful wastewater
treatment plants.
On the basis of the conclusions drawn from this first analysis, the
study proceeds to examine the return on the public investment in
operator training. Although it is possible to total the monies spent on
training, it is probably impossible to determine the definitive dollar
return from operator training, and certainly it was impossible to do
so within the resource limitations of this study. However, the public,
through federal and state agencies, has made a substantial capital
investment in the construction of wastewater treatment plants, and
training may be viewed as an expenditure to ensure the proper
utilization of these plants. These monies have been invested with the
expectation that specified quantities of wastewater will be treated to
specified levels of cleanliness. In this second investigation, training
was therefore viewed in terms of its ability to prevent or substan-
tially reduce faulty operations that might dissipate the public
investment through delivery of an effluent of substandard quality or
impairment of plant capability or productivity.
The conclusions and recommendations derived from these two
investigations have been presented in Parts I and II, respectively, of
this report. Section B of this part describes the various research
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activities that were conducted in support of these investigations. The
results of the research and analysis are presented in detail in the
remainder of this report, as follows:
Part IV: The Impact of Operator Training on Waste-
water Treatment Plant Performance
Part V: The Return on the Public Investment in
Wastewater Treatment Plant Operator Training
8. Research Methodology
Because a study of this nature required uniformity and compatibility
of data, and because the scope of the study was necessarily limited,
all of the work was performed within one state. The state of Texas
was selected because it contains a particularly large number of
treatment plants, has received considerable federal operator training
funds, and is very advanced in its policies and procedures relating to
water pollution control.
1. The Impact of Operator Training on Wastewater Treat-
ment Plant Performance
The initial hypothesis for this portion of the study was that the
relative effectiveness of training could be determined by an examina-
tion of "paired" plants that were similar in all design characteristics
except that one of them was staffed by trained operators and the
other staffed by untrained personnel. Upon initial investigation in
Texas, this approach was rejected since it was impossible to establish
pairs in which the training factor was the only independent variable
affecting effluent quality. Other variables that precluded pairing
included plant capacity, load, type of treatment, age and condition
of the plant, and level of staffing (in comparison to design
standards) each of which tended to combine with the others in a
unique way for each plant. Therefore, the approaches described
below were developed and implemented.
a. The Effectiveness of Training in Improving Perfor-
mance. Examination of the impact of training in improving perfor-
mance was complicated by the lack of consistent data as the basis for
a statistical sampling of plants across the state of Texas. No single
source of information exists that presents training completed or level
of operator certification achieved together with plant performance
within Texas. Existing sources of information available from separate
state agencies (described below) present time-series data for plant
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performance and cross-sectional data on operator certification and
training as of the end of 1971. These data had to be manually looked
up and cross-filed to get complete data on each plant to be studied.
Therefore, a survey of the results of operator training in all of the
municipal treatment plants in Texas would have been impossible
within the resources available for this study. Accordingly, an
approach was sought to identify specific plants where training might
well have had a specific effect and then to determine the details of
that effect by "before" and "after" training analyses. The specific
approach initiated was two pronged.
(1) "Operation Cleansweep" Analysis. First, 1971
and 1972 performance was analyzed for 16 plants whose perfor-
mance had been so poor during the first quarter of 1971 that they
had been summoned by the Texas Water Quality Board's (WQB's)
"Operation Cleansweep" project to explain the reasons for their
substandard performance and to devise possible solutions. The
theory of this examination was that operator training might well
have been instituted as a performance remedy in these plants.
(2) WQB District Supervisors Survey. To supple-
ment this analysis, the 12 district Texas WQB supervisors were
surveyed to obtain professional opinions as to which plants had
benefited from operator training since 1970. Although the resulting
sample of 51 plants does not necessarily include every plant in the
state that benefited from training during the specified period and was
not selected according to random statistical methods, it does permit
an assessment of the types of plant performance and operator
behavior improvements that may be realized through training.
b. The Impact of Operator Training in Maintaining
Consistently High Performance. The effectiveness of training in
maintaining consistently high performance was approached through
computer analyses of relevant data on performance, certification,
and training available through Texas state agencies.
Computerized data from the WQB's self-monitoring reports main-
tained on a monthly basis yielded plant performance data with
respect to WQB-determined levels of capacity and treatment effec-
tiveness. Training Jevels were derived from computerized information
maintained by the Texas Department of Health which gave the name
and certification level of each certified wastewater treatment plant
operator, arrayed by town and certification level. Because
maintenance of certification is contingent upon completion of a
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quota of training hours within a time period, certification was used
as a surrogate for or indicator of the existence of training in this
analysis.
Plants were selected from the WQB printout for which at least six
months of performance data were available and which ranged in size
between one and twenty million gallons per day (MGD) in design
capacity. Then the number of certified operators at each level in the
town in which each plant is located were counted and merged with
the plant data to form a composite computerized data source relating
plant performance data to operator certification levels. For the
purposes of this study, it was necessary to assume that each operator
listed was employed by the wastewater treatment plant in the town
where he worked.
2. The Return on the Public Investment in Wastewater
Treatment Plant Operator Training
An attempt was made to develop some quantitative insights into the
dollar value of the benefits that can be derived from operator
training. The scope of this study precluded estimation of the precise
dollar value of such benefits. However, it was considered possible to
develop numbers that would be useful to decision-makers considering
the desirability of sponsoring and/or conducting additional operator
training.
The value of training benefits was viewed from two points of view.
First, the value of the capital assets entrusted to the care of
individual operators in Texas was estimated on the basis of data
obtained through the EPA STORET information system, the Texas
Water Quality Board, and current literature. Second, the capital
investment that is wasted when a treatment plant does not fulfill its
BOD and TSS removal specifications was estimated on the basis of
Texas WQB performance data on plants known to have experienced
performance improvements following operator training.
Both of these approaches emphasize the value of operator training by
comparing the relative value of training benefits to the estimated cost
of training individual operators. In effect, training cost is-viewed as
the cost of insuring that capital investment will be used properly and
effectively to produce the intended returns in terms of effluent
quality.
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3. Validity of Study Conclusions
This report is a first in its attempt to make a quantitative assessment
of the effectiveness of wastewater treatment operator training and to
determine the cost effectiveness of such training. Despite the
limitations of the research data base, the conclusions appear very
strong that training can have a key role in improving performance if
properly utilized and in maintaining consistently high performance
where good performance has been previously established. In addi-
tion, regardless of the measure of value that is used, the economic
return from training in relation to its cost is enormous. It is expected
that a broader scale investigation either within the state of Texas or
throughout the country would only add further evidence in support
of these conclusions.
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PART IV
THE IMPACT OF OPERATOR TRAINING
ON WASTEWATER TREATMENT PLANT PERFORMANCE
The response of an operator to formal training and the response of
plant performance to a newly trained or updated operator tend to be
unique to each combination of operator and plant. In this respect, it
is difficult to develop a formula which will express across the board
the impact that operator training may be expected to have on plant
performance. Therefore, in this report, training was viewed from two
perspectives:
Ability to improve faulty performance.
Ability to sustain high levels of performance.
In some cases, training can be identified as the only factor
influencing performance, while in others it acts in combination with
other stimuli (such as WQB pressure or new plant construction).
A. The Impact of Training in Improving Wastewater Treatment
Plant Performance
In an effort to gain an impression of the impact training might have
on performance, an examination of the Water Quality Board's
"Operation Cleansweep" and a survey of 12 WQB district supervisors
were conducted.
1. Operation Cleansweep
a. Overview. Operation Cleansweep is the WQB's on-
going project to upgrade the performance of Texas plants not
complying with Texas' standards of operation. The Board holds
monthly hearings on water quality problems and in the first three
months of 1971 brought 16 plants to testify as to the nature of their
performance problems and any corrective action that was either
planned or under way. These 16 plants all were drawn from five of
the 12 WQB districts in Texas; these five districts have a total
population of approximately 720 discharging plants, as revealed on
the self-monitoring reports filed monthly with the WQB.
t.
We have traced the histories of these plants subsequent to the
hearings to determine to what extent training may have had an
influence in performance improvement, where such improvement
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occurred, and to estimate the nature of the training benefits. The
problems which brought the plants there and the suggested remedial
actions were identified from the minutes of the hearings; the
subsequent history of each of the plants has been gained through
interviews with the surveillance staff in charge of these investigations
and the performance monitoring system of the Water Quality Board.
The 16 case histories developed during this investigation are
presented in subsection b, and the findings that emerged from the
Operation Cleansweep study are summarized in subsection c.
b. Operation Cleansweep Case Histories
Case 1
Town 1 had two severely overloaded plants and was summoned
before the WQB twice in the first quarter of 1971. One part-time
uncertified operator was in charge of both plants under the
supervision of a licensed municipal utilities director. Just prior to the
hearing, a WQB inspector had found in both plants poor effluent
quality, poor maintenance and operating practices, mechanical
reliability problems, high infiltration of the collection system
unnecessarily loading the plant, a high frequency of bypassing and
sewer overflows, and a failure to submit self-monitoring reports and
to report overflow incidents as required.
At the time of the hearing, the town officials agreed to explore the
possibility of joining a large river basin authority as a means of taking
some of the load off its two small plants.
Since the hearing this town has become self reporting and has
managed to get the river basin authority to take a small part of the
load from one plant and consider its application for membership, but
the two small plants are still overloaded. There was some improve-
ment in effluent quality in the balance of 1971, largely as a result of
the prodding and close supervision of WQB officers, but performance
was still below specification. Training has not been a factor in this
situation to date.
Case 2
The plant in Town 2 also lacked a certified operator and had a high
rate of infiltration and mechanical reliability problems when called
before the Board. Subsequently, the hiring of two properly trained
and licensed operators, the installation of lab equipment, and the
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enforcement of the town's industrial waste ordinance (resulting in
the closing of the major offending industrial facility) have all
contributed to dramatic improvement in the plant's performance in
1971. The plant is now compliant with WQB specifications. There is
no way to distinguish the influence of training from that of better
enforcement of the waste ordinance in this case, but WQB officials
have commented that without the trained personnel in place, the
necessary lab work and enforcement activities could not have been
carried out.
Case 3
This city's small plant was severely overloaded, and the results of the
WQB hearing indicated that the plant should both augment and
upgrade its facility. The town has not voted the necessary financing
for these changes, but the operators at the plant have managed some
improvement in effluent quality. The potential for training impact
after addition of new facilities is strong.
Case 4
This plant was determined to have poor quality effluent and needed
to augment its facilities to remedy an overloaded condition. Despite
this problem, censure by the WQB, and a change in management, in
early 1971 a bond issue for construction failed to pass. During the
rest of 1971, the plant managed to maintain an essentially constant
biological oxygen demand (BOD) and total suspended solids (TSS)
output despite increasing overloading. The potential for training
impact after addition of new facilities is strong.
Case 5
This small plant was consistently operating in noncompliance with its
permitted BOD and TSS levels. After being called before the WQB, it
hired a consulting engineering firm in April, and in October dramatic
performance improvement brought both BOD and TSS performance
to compliance levels. Training did not appear to affect this situation
directly.
Case 6
In the hearing before the Water Quality Board, this plant's poor
performance was attributed to defective mechanical procedures and
faulty or inadequate equipment. Following the WQB citation, a new
board of directors was appointed that committed itself to resolving
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the plant's performance problems. Subsequently the mechanical
operations improved, with an attendant improvement in effluent
quality, and the board of directors applied for a construction grant
to enlarge the facility. Although training was not applied directly in
the resolution of this plant's problems, the deficiencies noted by the
WQB in its citation requiring improvements in mechanical
processes and equipment are the types of improvements that might
' have been initiated automatically by a properly trained operator. The
potential for training impact after addition of new facilities is strong.
Case 7
This plant was not chlorinating its effluent sufficiently, but in other
respects its performance was satisfactory on BOD and slightly high
on TSS. An increase in chlorination in April 1971 cured the problem.
Performance on both BOD and TSS improved steadily through 1971,
largely as a result of operator training, particularly for the lead
operator in this plant.
CaseS
Like Case 7, this plant was not sufficiently chlorinating its effluent.
At the end of August 1971, however, heavier chlorination began, and
that problem has been resolved. BOD performance was not a serious
problem at this plant, but suspended solids performance was
noncompliant. During the year, operators of this large plant received
increased training and managed a noticeable improvement in TSS
measures, although they are not yet in compliance; some plant
renovations are required before full compliance can be achieved.
Case 9
This plant was not overloaded in 1971 (except for a one-month
seasonal peak), and its performance is well within the compliance
range. However, it was brought before the Board because of a serious
and worsening problem with suspended solids removal. Because the
problem is caused by industrial waste, the city has been told to pass
and enforce an industrial waste ordinance. It is expected that this
measure will cure the problem and that training is not a factor in this
case.
Case 10
This plant was and still remains seriously noncompliant on BOD and
TSS, and it began self-reporting only late in 1971. At the time that
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EXHIBIT I
SUMMARY OF OPERATION CLEANSWEEP CASE ANALYSIS
Case
1
T
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Problem
Overloading, others
Poor operation
Overloading
Overloading
Poor operation
Inadequate equipment
Low chlorine, non-
compliant TSS
Low chlorine, non-
compliant TSS
Heavy industrial
waste load
Poor operation
Poor operation
Deteriorated plant
Overloading
Overloading,
infiltration
Poor operation
Poor operation
Solution Selection
Offload
Hiring of trained
operators
Augment facilities
Augment facilities
Consulting engr.
Augment facilities
Chlorination and
training
Chlorination and
training
Industrial waste
ordinance
Training
Hiring of trained
operators
New plant
Regional affiliation
Consulting engr.
None taken
Chlorination
Apparent Influence
of Training
None
Strong
None
None
None
None
Moderate
Moderate
None
None
Strong
None
None
None
None
None
Potential Influence
of Training
None
N/A
Strong
Strong
None
Strong
N/A
N/A
None
Strong
N/A
Strong
None
None
Strong
None
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supervisors of the WQB. These men have surveillance responsibility
for monitoring plant performance and supervising or enforcing the
solution of individual pollution control problems. Typically they are
professional engineers and have engineers, former senior wastewater
treatment plant operators, and biological scientists on their staffs.
They report to one statewide authority, but they and their staffs
have a close and professional view of plant operations at the local
level.
The initial contact for this survey was made by memo from WQB
headquarters, followed by a telephone contact seeking specific
information on a case-by-case basis. Generally the WQB supervisors
gave us their impressions of plants which had benefited from training
without referring to specific data on personnel in their districts who
had been recently trained. Some supervisors from the larger districts
assembled notes summarizing the collective impressions of their
subordinates; others provided direct answers based upon their own
knowledge, and still others, while voicing strong support for training
as beneficial in many ways, did not describe specific case examples
from their districts. Where the number of cases described appeared to
be large and the supervisor wished to submit a return memo in lieu of
a telephone contact, this was accepted. In addition, actual visits were
made to two district supervisors with particularly interesting or long
answers.
The cases emerging from this survey reveal both the unique situations
and the common patterns which exist in plant response to training.
Each case is described in subsection b, and a summary analysis and
relevant conclusions are presented in subsection c.
b. Cases of Training Benefits Cited by WQB District
Supervisors
Plant 1 is a new plant which was off to a bad start with an operator
who did not understand how to run it. Following training, however,
and some assistance from a consulting engineer, the operator's
attitude and interest dramatically improved. Since the plant was new,
effluent quality had not been low but would have degraded over time
if the initial operator attitudes and knowledge had not been
improved.
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Case 2
The performance of this plant was dramatically improved as a result
of a combination of operator training and support from water
quality inspectors who have assisted the town in gaining control over
the industrial waste from a food processing plant. As a result of
training, the operator was sensitized to the problem and was able to
work with the surveillance agency to collect the data necessary to
effectively enforce its industrial wastewater ordinance.
ป Case 3
As a result of training, the operator of this older plant has given it a
face-lifting and now practices greatly improved maintenance pro-
cedures. Unfortunately, because of the plant's age, its performance
has not been improved.
Case 4
As a result of his training, the operator in Case 4 realized that his
plant was not physically capable of making its target. Nevertheless, in
order to get the best possible performance out of his facility, the
operator overhauled the plant and has managed to arrest the
performance degradation that had been taking place. In addition, in
order to avoid loading up the receiving waters with inordinately high
BOD and TSS loads, he has developed a revenue-producing irrigation
use for part of the plant effluent. Realizing also that a new plant was
the only long-term satisfactory solution, this operator has spoken at
meetings and has taken other actions to help the town to get a bond
issue passed for a new plant.
Case 5
As a result of training, this operator's attitude and "housekeeping"
practices have greatly improved. Because the plant is a no-discharge
plant that is, the effluent, if any, does not enter public waters
the performance could not be assessed.
Case 6
Operating difficultie's and neighborhood complaints of foul odors
have been eliminated by the operator in Case 6 since he completed
training. Prior to the training, the operator was shutting down
aeration blowers at night to save money thus rendering the
treatment process anaerobic. Blowers now run full time. Actual plant
19
-------
performance could not be assessed because the plant is a no-discharge
installation.
Case 7
Following training, this operator has acquired a new laboratory for
his plant, beautified its grounds, become concerned over compliancy,
and joined the required statewide self-monitoring program, in
addition to improving effluent quality. Prior to training, the plant
operator had not been submitting reports and, in fact, had been
discharging effluent into the wrong stream (of two that ran close to
the grounds), in violation of the plant's waste control order (WCO).
Case 8
As a result of training, the operator in this plant set up his own
laboratory. The training has created more interest in and understand-
ing of plant operations. Although the flow figures indicate that the
plant is operating at or slightly above its WCO specification, BOD
performance has dramatically improved (although somewhat at the
expense of TSS performance).
Case 9
Training has given this plant a certified operator and has enabled
him, with the support of some plant redesign, to greatly improve
BOD and TSS performance. Although the redesign of the plant was
accomplished professionally, the operator himself supervised the
rebuilding operations.
Case 10
Training provided this plant with a certified operator who set up a
new lab for his plant. Due to the seasonal loads on this plant and
occasional failures to report performance, it is not possible to detect
a change in performance.
Case 11
This municipality has instituted a policy of having all of its operators
trained to at least the lowest certification level. As a result of the
new policy and the resultant efforts to train all operators, strong
improvement in BOD performance has been noted and the plant is
now fully compliant on both BOD and TSS.
20
-------
Case 12
Training provided this plant with a certified operator who has
improved both BOD performance and plant appearance. He has also
assumed the responsibility for his own lab work.
Case 13
Training provided for the certification of an operator at this plant.
With his new knowledge, the operator has been able to dramatically
improve his BOD performance and make some improvement in his
TSS performance.
Case 14
Since this operator returned from training, he has exhibited greater
enthusiasm for his job and plant performance has improved on both
BOD and TSS.
Case 15
This plant has a laboratory which was unused prior to operator's
attending a training program. Following the program, he is now
performing his own lab work. Although plant performance was
satisfactory at the outset, further improvement in plant performance
has been noted.
Case 16
Training has helped the supervisor of this plant move up to a B
certificate and has influenced him to plan for the establishment of a
plant laboratory. Although TSS performance has continually been
satisfactory, BOD levels are now compliant, and performance on
both measures has been improving steadily since the completion of
training,
Case 17
The operator of this plant has made a notable improvement in his
knowledge as well as in plant performance. BOD levels, which were
originally satisfactory, are now well within required levels, and TSS
has been brought from a substandard level to well within the
compliance range.
21
-------
Case 18
Training upgraded the license of one operator at this plant, as well as
providing him with an opportunity to improve his reading and
writing abilities, which were originally marginal. In addition, plant
maintenance has been improved. Performance change could not be
assessed because the plant is a no-discharge facility.
Case 19
Training provided this plant with one upgraded operator and six
newly certified operators. Although plant performance has been
consistently compliant, the training has given the operators the skills
to improve maintenance.
Case 20
Training programs have allowed seven operators to upgrade their
licenses and two more to become certified. Although the supervisor
of the plant claims to see no performance improvement, the WQB
self-monitoring report shows an improving but still-noncompliant
effluent.
Case 21
Through training, this large plant managed to upgrade 19 operators
in pay and status. Unfortunately, because the plant is a no-discharge
installation, differences in performance could not be observed, but
better housekeeping and maintenance around the plant have been
noted.
Case 22
The plant also upgraded its operator through training, and an
improvement in maintenance and housekeeping has been noticed.
Performance improvement could not be assessed, however, because
this plant is a no-discharge facility.
Case 23
Maintenance and housekeeping at this no-discharge plant improved as
a result of training. No performance change could be measured.
22
-------
Case 24
This plant has a certified C operator who takes every chance to go to
the courses offered, attend meetings of local operators, and assist
neighboring operators, despite the fact that he has town duties in
addition to wastewater treatment plant operation. The performance
of this plant is remarkable in the low BOD levels it has achieved, and
the operator managed a significant improvement in TSS performance
during 1971.
Case 25
By hiring two trained and licensed operators and enforcing its
industrial wastewater ordinance, this plant managed a sufficient
improvement in both BOD and TSS performance to progress from
noncompliant to compliant status. (This case is a sample plant as
Case 2 of the Operation Cleansweep Survey.)
Case 26
Through training, the operator of this plant gained certification. This
man achieved compliant operations early in 1971 and continued to
improve BOD performance throughout the year.
Case 27
This town abandoned its old plant and hired a new full-time certified
operator to replace the three garbage collectors who had been
tending the old plant on a part-time basis. The new trained and
certified operator has been able to improve his performance
consistently, bringing BOD and TSS effluent levels down to
exceedingly low levels.
Case 28
In the two years before being called before the Water Quality Board,
this plant had not had a certified operator and had been experiencing
BOD levels in excess of 170, with TSS at 66 in early 1969. At this
time, sludge banks were observed regularly in the stream into which
the plant effluent was discharged. The hiring of a different but still
unlicensed operator in 1970 improved operations somewhat, but
performance still fluctuated and sludge beds were cleaned
inconsistently.
The present operator was unlicensed when hired but had a letter in
training the equivalent of a license prior to completion of
23
-------
sufficient experience to qualify for certification. Following several
months of work, he attended a technical operations and maintenance
training school for six weeks. Following training, plant operations
improved from noncompliant to well within compliance levels on
BOD, although TSS is still noncompliant.
Case 29
Through training of its operators, this plant, although overloaded,
has managed to achieve compliant BOD and TSS performance most
of the time. It does, however, have some equipment design problems
which cause excessive bypassing to occur.
Case 30
As a result of training, this operator converted his plant from a
discharging to a no-discharge installation by adding a pond to catch
the effluent - thereby avoiding discharging the effluent into public
waters.
Case 31
Training of one of the two operators in this facility has improved
BOD performance from noncompliant to compliant. TSS perfor-
mance has no compliance specification and does not appear to have
changed in the period during which BOD performance has improved.
Case 32
This older plant achieved compliant performance as a result of
operator training (although the operator has not yet qualified for
certification). Following his training, the operator greatly improved
BOD performance, which had been noncompliant. He also tfiade
some improvements in TSS, which had already been satisfactory as a
result of a generous limit in the plant's permit. A big improvement in
housekeeping has been noticed.
Case 33
An older licensed operator in this plant was replaced by a newly
trained and licensed man who cleaned up the plant and equipment
thoroughly and improved BOD performance from noncompliant to
compliant. Data on TSS performance were not available.
24
-------
Case 34
As a result of training, this plant's operators previously uncerti-
fied are now licensed. Plant performance has steadily improved on
BOD to within compliance levels and remained steady on TSS, which
is still slightly substandard.
Case 35
As a result of training, the operator of this plant received
certification and demonstrated an improved attitude and motivation
toward his work. Following training, he improved the appearance
and general maintenance of the plant. Because the plant is a
no-discharge facility, specific performance figures are not available.
Case 36
In this large plant, previously uncertified operators gained certifica-
tion, and certified operators upgraded their licenses as a result of
training. Improved general maintenance has been observed, and the
plant's performance on both BOD and TSS has changed from
noncompliant to well within compliance limits.
Case 37
Training in this case enabled an operator to gain certification, and he
has exhibited increased interest and motivation. No performance
information on this plant was available because it is not self
reporting.
Case 38
The acquisition of certification by the operator of this plant after
training has led him to show improved motivation and interest in his
work. Since completing training, he has improved or renovated parts
of the plant, and BOD (already compliant) and TSS performance
appear to have improved somewhat, although the WQB has not yet
specified a TSS compliance standard for the plant.
Case 39
M.
This plant's operator achieved certification and exhibited improved
motivation after receiving training. He improved general maintenance
around the plant and has brought BOD performance into compli-
ance. TSS performance has improved but still remains noncompliant.
25
-------
Case 40
This plant's operator, as a result of training, upgraded his license and
has been exhibiting stronger motivation and higher morale. In
addition, the plant performance has improved on both BOD and
TSS, although the plant is still noncompliant on both measures.
Case 41
This plant has had its operator certified through training. In addition
to showing increased motivation, he has improved maintenance and
has raised BOD performance from noncompliant to compliant
somewhat at the expense of TSS performance (for which WQB had
not specified a target).
Case 42
At this plant, new operators gained certification and at least one
operator upgraded his license. Both motivation and BOD perfor-
mance have improved, although BOD performance was originally
compliant. TSS performance is somewhat noncompliant and has
remained virtually unchanged.
Case 43
The operator of this no-discharge plant received a new operator
certification and displayed improved attitude and morale following
training. Performance improvement could not be determined, be-
cause of the no-discharge nature of the plant.
Case 44
Training provided both new and upgraded operator certificates for
the operators at this plant. Aided by new treatment facilities, these
operators have maintained consistently a very high quality effluent
on both BOD and TSS.
Case 45
Training allowed the operator of this plant to upgrade his certificate.
As a result, he displayed notably higher morale and motivation and
made improvements in plant maintenance. He improved BOD
performance from noncompliant to compliant; TSS performance had
no specification but appeared to be getting slightly worse.
26
-------
Case 46
An upgraded operator certificate and improved maintenance and
attitude were the benefits of training for this plant. Effluent quality
had been satisfactory and remained consistently good.
Case 47
Upgrading of an operator certificate and the certification of a new
operator were achieved as a result of training. Attitudes improved
and BOD performance, which had been somewhat erratic, settled
down to a position well within the compliance range. TSS perfor-
mance has remained compliant.
Case 48
Following training, this plant's operator became newly certified and
exhibited an improved attitude toward his work. He renovated parts
of the plant and generally improved maintenance. Erratic BOD and
noncompliant TSS performance settled down to values well within
compliance ranges.
Case 49
This plant's operators became newly certified and motivation
improved as a result of training. Maintenance procedures improved,
and plant renovation was undertaken. BOD performance, which was
borderline compliant, improved to well within compliance
tolerances. TSS performance was not specified in the permit and did
not change significantly.
Case 50
The operator of this plant who had already been effective prior to
his recent training has begun to do his own lab work. Performance
figures show some recent degradation in both BOD and TSS, but it
could not be determined whether this was an actual decline in
performance or the result of operator inexperience with lab
procedures.
Case 51 '
This plant hired a properly trained and certified operator who made
strong progress in cleaning up the effluents making it compliant on
TSS. The plant was originally compliant on BOD but has further
27
-------
improved its performance on this measure. (This case is the same as
Case No. 11 in the Operation Cleansweep Survey.)
c. Findings from the District Supervisors Survey.
Among the 51 cases cited by the district supervisors as demonstrating
performance improvement through training, a number of common
patterns were observed. These are categorized in Exhibit 2.
In nearly all of the cases 48 of 51 training served to boost
operator morale, attitude, or motivation for his job. Such changes are
rated as "General Improvement" in Exhibit 2.
Attitude changes alone have yielded significant benefits. As one town
manager put it, "I can get honest and informed answers from
operators who are more sure of themselves. They can tell me their
problems, and they can work more effectively with the consulting
engineers when they need to be called in to solve plant expansion or
design problems. Without the knowledge gained from operator
training, these men are embarrassed and defensive about their
operation of the plant and consequently much harder to understand
and work with."
A second aspect of the better attitude is a generally cleaner plant.
One of the most frequent comments heard was that the operator, or
supervisor, upon his return from school, had policed the grounds and
brightened up the plant through washing, painting, and renovating
the buildings and other facilities.
In the "Other Improvement" category on Exhibit 2, at least seven
plants had decided to carry on their own lab work as a result of
operator attendance at a lab school. This is the only area of
substantial operating cost reduction resulting from training that was
observed during the study. It was reported by a number of WQB
representatives and plant operators that lab work, when performed
by an outside source, costs, on an average, about $600 per year on a
contract basis. If the trained operator performing his own laboratory
work spends as much as $100 per year on supplies and equipment, he
will be saving most of this contract amount a sum representing a
substantial and ongoing return on investment in his laboratory
training.
Two plants which appeared in the "Other Improvement" category
have managed to employ some innovative tactics to benefit their
operations. One was converted to a no-discharge plant by the
addition of a pond, and the other found a market in irrigation for its
28
-------
EXHIBIT 2
SUMMARY OF WQB SUPERVISOR SURVEY CASE ANALYSIS
Case
1
1
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Became
Compliant
-
-
-
-
-
-
-
X
-
-
X
X
-
-
-
X
X
-
-
-
-
-
-
-
X
Improved
Effluent
Quality
X
X
*
*
X
X
X
**
X
X
X
X
X
X
*
X
*
*
X
X
General
Improvement
X
X
X
X
X
X
X
X
X
X
X
X
X
X
-
X
X
X
X
X
X
X
X
X
X
Other
Improvement
-
-
-
X
-
-
X
X
-
X
-
X
-
-
X
X
-
-
-
-
-
-
-
-
-
Comment
Developed irrigation market
source for effluent
Independent lab capability
Independent lab capability
Independent lab capability
Independent lab capability
Independent lab capability
*No-discharge facility.
**Self-reportirg data not complete.
29
-------
EXHIBIT 2 (Cont'd)
Case
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
Became
Compliant
X
-
X
X
-
X
X
X
-
-
X
-
-
X
-
X
-
-
-
X
-
X
X
X
-
X
Improved
Effluent
Quality
X
X
X
X
*
X
X
X
X
*
X
**
X
X
X
X
X
*
X
X
X
X
X
General
Improvement
X
X
-
X
-
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Other
Improvement
-
-
-
-
X
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
X
-
Comment
Conversion to no-discharge facility
Independent lab capability
No-discharge facility.
"Self-reporting data not complete.
30
-------
effluent. These approaches benefit the public because the effluent no
longer enters public waters, but they do not directly indicate plant
performance improvement as a result of training.
Of the 51 plants mentioned by the WQB district supervisors as having
experienced training benefits, 10 were either no-discharge facilities or
reported inadequate effluent data during 1971 to permit quantitative
performance assessment. Of the remaining 41 plants, 33 experienced
marked improvement in effluent quality; 17 of the plants whose
effluent improved also became compliant on both BOD and TSS
following operator training, as indicated on Exhibit 2. (Two of the
plants that improved effluent quality and became compliant had
been called before the WQB as part of Operation Cleansweep in the
first three months of 1971.)
Summarizing these results, of 51 plants which were identified as
having benefited noticeably from training:
(i) Two cited for noncompliance by Operation Clean-
sweep in early 1971 became compliant; 15 more not
cited by the WQB improved their operations from
noncompliant to compliant. A total of 33.3 percent
of the sample became compliant on both BOD and
TSS following training.
(ii) Thirty-three (64.7 percent of the sample), including
all 17 in (i) above, experienced improvement in
effluent quality.
(iii) A total of 48 plants 94.1 percent - experienced
"General Improvements" of noticeable proportions.
(iv) Nine plants eight of which experienced at least one
of the above benefits experienced "Other Improve-
ments" (including two that modified their plants to
prevent them from discharging effluent into public
streams).
(In this summary, the total benefits listed exceed 51 in number
because of multiple effects experienced by individual plants.)
31
-------
B. The Impact of Training in Sustaining High Wastewater
Treatment Plant Performance
The influence of training as a factor in sustaining high levels of
treatment plant performance was explored through a computer
correlation analysis for 124 wastewater treatment plants between
levels of performance of various factors representing number of
operators employed and number of trained and certified operators
who exercised a direct influence over the operations of each plant.
1. Correlation Data Base
Three types of data were acquired for correlation in this analysis:
Plant performance.
Operator staffing.
Operator training (certification).
The Texas WQB maintains a "self-monitoring" system to which every
plant licensed by the state that discharges effluent into a public
stream or waterway must report monthly. These reports contain
information on many items of plant performance, including
maximum and average flow experienced by the plant; bypassing
activity, if any; the percent of effluent discharged to public waters;
and the maximum and average BOD and suspended solids in the
effluent in parts per million. The report from each plant is fed into a
WQB computer which produces printouts of plant performance data
over a running 12-month period for all plants, both municipal and
industrial. (This investigation concerned itself only with municipal
plants.) A typical entry for one plant in the WQB is shown in Exhibit
3.
As a basis for selecting a sample for the correlation analysis, four
criteria were established:
(i) Size between 1.0 and 20 million gallons per day
design capacity.
(ii) Accurate performance data available for at least six
months of 1971.
(iii) Operator staffing information independently available
(see below).
32
-------
EXHIBITS
TYPICAL PLANT ENTRY IN WQB
SELF-MONITORING COMPUTER REPORTS
u>
REPORT DAYS DAYS VOL-MAX
DATE DISC BYPASS BYPASSED
GALENA PARK CITY OF
ri-7i
02-71
"3-71
04-71
P5-71
"6-71
C7-71
11-71
n^-71
10-71
11-71
12-71
31
28
31
30
31
3"
31
31
30
31
30
31
oo
00
CO
00
00
00
00,
00
no
00
oo
00
FLOW-HAX
HG/OAY
.400
.600
.$ni
.350
.440
.360
.340
.310
.40"
.300
.500
.320
REQUIREMENTS
W-AVF
/DAY
VOL
RELEASED
10031-01
.330
.340
.350
.300
.300
,?ซP
.250
.225
.750
.750
.290
.250
.700
100
100
10P
100
100
100
100
100
100
100
100
too
BOD
MAX
PLANT
Q
B
7
29
26
13
6
1*
R
4
R
2
30
BOD
MOAVE
NO 1
9
8
6
23ป
21*
R
6
10
5
It
a
2
20
TSS
MAX
18
14
9
41*
38*
21
6
6
7
11
10
7
30
TSS
MOAVE
15
11
7
30*
27*
15
4
5
6
8
7
6
20
CHL-RES
HIN
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
1.0
2.0
2.0
1.0
1.0
CHL-RES
HOAVE
2.0
2.0
2.0
2.0
2.0
2.0
2.0
1.4
2.0
2.0
2.0
2.0
1.0
STA
HIN
50*
37
37*
37*
37*
21*
21*
21*
50*
60*
50*
50*
95
STA
MOAyE,
60*
53
58*
50*
40*
37*
40*
40*
55*
65*
65*
65*
95
S-SO
MAX
*
4
2
S-SOL SPEC
HOAVE PROV
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Nป
NA
3
-------
(iv) Operator training (certification) data independently
available (see below).
A total of 124 plants out of a state population of over 1,200
discharging facilities fulfilled these four requirements.
Operator staffing information the number of operators employed
full or part-time was taken from manpower surveys performed for
the Environmental Protection Agency and Department of Labor in
1971, and certification data were taken from the Texas Department
of Public Health records. Certification data were used, in this study,
as a surrogate or indicator of operator training because of the direct
connection between the two under Texas licensing regulations and
the lack of readily usable data on training itself.
In Texas, operators are certified at four different levels, as shown in
Exhibit 4. The B, C, and D operators, to maintain their certificates,
have to have achieved the directly related training shown under
"Renewal Provisions" in Exhibit 4. Thus, a D operator has to have an
average of five hours per year training; a C, 6 2/3 hours; and a B, 10
hours simply to maintain their status. Furthermore, the training that
is accepted for credit under this plan is approved by a professional
committee within the state which insists that the training be directly
related to job responsibilities, not just generally applicable. The
operators who have currently valid certificates can therefore be
considered to be trained and in fact recently trained operators.
Those who do not possess certificates, of course, may be partially
trained, and those who do have them may be trained above the
minimum levels in effect on their way to a higher level. Therefore,
although the existence of a certificate is not a precise measure of the
level of training, it is, we feel, a reliable indicator of the existence of
training.
2. Computer Correlation Analysis
The computer correlation study, based upon the inputs above,
revealed that both staffing and training did influence plant opera-
tions and that it influenced some types of plants more than others.
Heavily loaded plants were apparently affected more than lightly
loaded ones, and activated sludge plants more than biological filter
plants.
The first step in the analysis was the calculation of a correlation
matrix to determine which parameters of performance, staffing, and
training seemed to be related. In the matrix, a series of correlation
34
-------
EXHIBIT 4
OPERATOR CERTIFICATION REQUIREMENTS IN TEXAS
Class
A
B
C
D
Requirements
Education Masters Degree
Experience 4 yrs. o
Training 160hr.
Education Bachelor Degree
Experience 1 yr. c
Training 60 hr.
Education 1 -year College
Experience 2 yrs. o
Training 0
Education HS/GED
Experience 0 <
Training 1 0 hr.
Bachelor Degree ( 2-year College
r 5 yrs. or 6 yrs. (
160hr.
HS/GED
r 3 yrs
lOOhr.
HS/GED
r 3 yrs. o
0
160hr.
HS/GED
r 2 yrs. <
20 hr.
Less than HS/GED Less than HS/GI
r 1 yr. or 0
1
0 , 20 hr.
HS or GED
r 8 yrs.
160hr.
HS/GED
r 1 yr.
40 hr.
D
Renewal
Provision
NONE
SO hours in
5 years
20 hours in
3 years
10 hours in
2 years
Source: Texas State Department of Health, Division of Sanitary Engineering, Rules and Regulations Covering the
Certification of Water Utilities Personnel, adopted by the Texas State Board of Health, September 12,
1966, revised June 8, 1969, and December 12, 1971.
-------
coefficients was calculated which indicated the apparent relationship
existing between pairs of parameters. If a nearly perfect linear
correspondence existed, the coefficient approached + 1.0000; if very
little relationship existed, the coefficient approached 0.0000. For
purposes of this analysis, we have assumed that strong correlations
exist where the coefficient is 0.7 or more, that weak to moderate
relationships are represented by coefficients between 0.4 and 0.7,
and that no meaningful relationships exist if coefficients are below
0.4. A positive coefficient indicates that the variables are moving in
the same direction and a negative one that the variables are moving
inversely to one another.
The parameters of performance, staffing, and training used in the
analysis include the following:
PER 1 BOD performance; the inverse ratio of BOD
achieved to BOD permitted, resulting in a higher
number as performance improves.
PER 2 - TSS performance, calculated like PER 1.
LOADING Plant load; the average flow divided by the
WCO-permitted flow, resulting in a fully loaded plant
exhibiting 1.0, overloaded plants more than 1.0, and
underloaded plants less than 1 .0.
OPL Operator staff; the number of operators (whether
or not certified) per plant.
INT Staffing intensity; the number of operators
(whether or not certified) divided by the average
flow.
TI, T2, TS, T4 - Certified operators; the number of
operators per plant at the D, C, B, and A levels,
respectively.
TlA> T2A. TSA, T4A Certified operator intensity; the
number of operators certified at each level divided by
the permitted flow.
TIB, T2B, TSB, T4B - Certified operator intensity, cal-
culated as above but divided by the average flow.
36
-------
TIC, T2C, TSC, T4C - Certified operator density; the
number of certified operators at each level, divided
by OPL, the number of operators employed.
TReq, TB, TC The values for the sum of certified
operators at all levels divided, respectively, by per-
mitted flow, average flow, and operators employed.
TlND - Training index; an index of the numbers of
certified operators, weighted according to average
training hours required for each level of certificate,
divided by permitted flow TI + 2T2 + 4Ts + 8T4
Required Flow
The A sample matrix presenting correlation coefficients for over-
loaded trickling filter plants between various pairs of these and other
factors is presented in Exhibit 5. Coefficients used in later analyses
are flagged.
The computer correlations yielded the data shown in Exhibits 6, 7,
8, and 9. Exhibit 6 shows to what extent performance, represented
by PER 1 and PER 2, correlates with staffing levels, as represented
by INT. Applying the above criteria for identifying the strength of
correlations from these data, we find that there appears to be a weak
to moderate correlation between number of operators and perfor-
mance in overloaded trickling filter plants and in fully loaded
"other" plants (at least in the removal of suspended solids). On the
other hand, the performance of activated sludge plants operating at
more than 50 percent of rated load and moderately loaded "other"
plants appears to be inversely correlated (at weak to moderate
strength) with number of operators. These findings suggest that
overloaded biological filter plants and fully loaded other plants are
more labor intensive than activated sludge plants and that the
addition of labor in those plants, whether or not trained, will help
performance to a degree.
Exhibit 7 shows the correlation coefficients for TIA, T2A,
T4A, and TReq with PER 1 and PER 2. These represent the extent
to which performance correlated with the number of certified
operators at each of the four certification levels and in relation to
total permitted gallons of flow per day. From these data, it can be
seen that certified operators appear to be slightly more influential (as
judged by the frequency of positive correlations observed) in the
operation of activated sludge plants (7 positive correlations above
0.4) than in the operation of either trickling filter (4 positive
37
-------
EXHIBIT 5
SAMPLE COMPUTERIZED CORRELATION MATRIX
(For Overloaded Trickling Filter Plants)
CORRELATION MATRIX:
- Performance Parameter*.
FLO
1 PER 2 1-*-*
FLO
REQ
BOO
Ttt
OPL
LAB
S
1.0000
-0.4647
03684
03898
-04198
0.1187
03459
-04053
-0.1499
05197
0.4483
-0.1880
03377
-0.4762
0.3340
0.8827
-03973
05273
03184
J- 0.4296
0.104
0.0
ซ 0.0
* OjO
T1A J 0.0
jฃ OjQ
uj 1031 n.a.
T2
T2A
T3
T3A
T4
T4A
TREQ
TB
BODREO
TSSREO
PERI
PER 2
0.8903
0.3433
03333
0.4647
13000
104304 1
02096
-0.3948
-03929
-03239
- 0.1757
1-03882 1
05696
-05019
-0.1994
03919
03485
1-0.27401
-0.4998
0.1983
1- 0.13621
-0.4994
03178
1-056731
05463
03407
0.7420
0.5661
0.1469
0.7277
-03036
0.3469
0.6561
0.0564
04304
. 15000
TIHD | -03653
S -0.1017
U- -03761
TIND1 ซฐ -04328
2 05458
ฃ -0.1960
LOADING JS 0.1122
-03622
INT
TIB
T2B
T38
T4B
03014
-03253
- 0.0695
05167
OJO
QXI
IQjOl IM,
-04438
05729
[7331741
-03313
-0.1898
1-038081
03368
I- 03512 1
REQ
P
TIHD
05898
03095
-0.3663
1.0000
03364
-03440
03383
03042
-03745
05078
03456
-03433
03699
0.1775
-03370
0.7340
0.4868
-0.0822
03431
0.1433
-03756
0.0
0.0
0.0
OJO
0.0
0.0
0.6552
-0X1101
-0.3843
-04196
-0.3948
-0.1017
03384
1.0000
0.7824
-0.3024
0.7898
05727
03128
0.1898
-0X1774
03498
0.1090
0X1330
-04633
0.6407
. 05486
-0.4504
03353
03349
0.0823
-0.1892
-0.1795
03174
0X1955
-03035
-0.1760
-0.1633
-0X1272
0.1187
-03929
-03761
-03440
0.7624
1.0000
-04010
0.7129
03642
03005
-04811
-0.4657
-0.1518
0.1779
0.1921
0X1
05
0X1
-03821
03337
0.0525
03066
0.7922
0572S
03102
0.1103
0X1611
JOB-
T3A
TIND1
03459
0.3238
-0.4328
03393
03024
-0.4010
1.0000
03663
-0.3601
03621
-03146
-03179
0.6968
-03048
-0.4161
03818
0.0388
0.0273
0.7372
-03437
-0.4451
0.0
0X1
0.0
0.0
0X1
03
03667
-0.3985
-03253
-0.4053
-0.1767
0.0459
03042
0.7898
0.7129
0.2663
1.0000
05753
0.6139
-0.1797
-03949
03507
-0.1089
-03330
-04057
05242
05823
-04105
03059
03681
05390
-03050
- 0.1316
03203
0.1858
0.15E8
-04370
-0.0194
03578
-0.1499
-03882
-0.1960
-03745
03727
05642
-03601
05753
1.0000
03146
-04007
0.4654
-03532
0.1816
0.1687
05
0.0
05
-03800
-0.1339
0.0823
-03773
03985
05752
03974
-0.0841
-03030
TSS
T4
LOADING
05197
03696
0.1122
03076
03128
03005
05821
05139
0.0146
15000
0.5717
0.0256
0.7054
03340
-03673
03705
-05330
-03639
0.7466
03459
0.0628
0.0
0.0
03
0.0
05
05
03624
0.0251
-03829
-0.4463
03019
-03622
0.3456
0.1898
-04611
-03146
- 0.1797
-04007
05717
13000
0.1559
03060
03279
0.0462
-03785
-03985
05196
03848
-03146
-0.6136
0.0272
-0.1410
-0.1926
03999
-0.0101
-03161
-0.3437
-03898
03366
-0.1680
-0.1994
-03014
-03433
-05774
-04667
- 0.3179
-03949
-0.4654
0.0266
0.1559
1.0000
-03171
-0.0974
0.4275
05
0.0
0.0
-04287
-04758
-0.4241
-03222
-0.1901
-04268
03470
0.7582
-05109
OPL
T4A
INT'
03377
03919
-03253
03699
03498
-0.1618
0.6988
03807
-03532
0.7054
03060
-0.3171
15000
03326
03862
03721
-0.1985
0.0174
03144
03996
0.1114
0.0
03
0.0
0.0
03
03
03613
-03200
0.0118
- 0.4762
03465
-0.0695
0.1775
0.1090
0.1779
-03048
-0.1089
0.1816
03340
03279
-03974
03326
13000
0.0689
-04802
-03236
0.1627
04398
-03202
03465
03453
0.1622
0.4321
05730
-0.1590
0.1979
0.0219
-03179
05107
03340
03740
03187
-0.3370
0.0330
0.1921
-04161
-03330
0.1687
-03573
05462
-0.4275
03862
0.0689
1.0000
03
03
03
-03942
-03032
05600
-03021
-0.1090
03087
0.3099
0.9898
0.1241
LAB
TREQ
TIB
0.6927
04998
03
0.7340
-0.4633
05
03616
-0.4057
05
03706
-03785
05
05721
-04802
05
13000
-0.1207
05
03694
-03031
03
0.0
0.0
0.0
05
0.0
0.0
05554
03783
0.0
-03973
0.1983
0.0
0.4868
0.6407
05
05388
05242
05
-0.0330
-03985
0.0
-0.1985
-03236
0.0
0.1207
1.0000
03
-0.0913
03906
0.0
05022
- 05770
0.0
05554
-0.1446
05
03520
0.0935
05
03273
-0.1382
0.0
-03822
05486
05
-05273
03823
0.0
-03639
-05196
05
05174
0.1627
05
03
05
05
03614
03344
05
05S26
05254
0.0
0.1930
0.1901
0.0
S
TB
T2B
03184
04994
-04436
03431
-0.4504
-03821
0.7372
-0.4105
0.3800
0.7465
-03848
04287
05144
-04388
03942
03594
-0.0913
-03614
13000
-04817
-03966
05
0.0
0.0
0.0
0.0
0.0
05334
-03367
03824
-0.4296
03178
05728
0.1433
0.6353
-03337
-03437
05069
-0.1339
03459
-03145
-04758
03996
03202
-03032
-05031
03906
03344
-04917
15000
03808
0.1410
-0.0083
04395
04815
-03942
03175
0.1020
0.1597
04148
0.1834
-05673
05174
-03758
05349
0.0525
-04451
03681
03823
03628
-05136
04241
0.1114
03465
0.0600
03
0.0
03
-03966
03808
1.0000
-03394
05121
0.1239
03729
- 0.1814
0.4787
Tl"
BODREQ
T38
03
03483
03313
05
03823
03086
03
0.0390
-03773
05
0.0272
-03222
03
03453
-03021
05
05022
03526
05
0.1410
-03394
05
0.0
0.0
05
05
0.0
05
05306
-03935
05
03407
-0.1899
0.0
0.1692
0.7922
0.0
-03050
03995
05
-0.1410
-0.1901
03
-0.1622
-0.1090
05
-05770
03254
05
-0.0083
05121
05
1.0000
0.1930
05
03273
- 0.179G
03
0.6070
0.0090
03
0.7420
-03806
05
-0.1795
05725
05
-0.1316
05752
05
-0.1826
-04268
05
04321
03087
0.0
03
05
03
0.4395
-0.1238
05
- 0.1930
13000
05
-0.1771
- 0.0821
itsBiU-*-
T48
03
03651
03388
03
0.6174
03102
05
03203
03974
05
03999
03470
05
05730
03099
05
05554
-0.1930
05
04815
03729
03
0.0
03
05
03
0.0
05
0.7899
-03284
05
0.1459
03248
05
05955
0.1103
05
-0.1858
-05841
05
-0.0101
0.7582
0.0
-0.1590
05898
03
-0.1446
- 0.1901
05
-03942
0.1814
05
0.6273
0.1771
05
1.0000
-0.1544
05
03423
-03318
03
0.7277
-03532
05
-03035
03611
05
-0.1558
-03030
05
-03161
-05109
03
0.1979
0.1241
03
05
0.0
0.0
03175
-04787
05
0.1796
-05821
0.0
0.1544
1.0000
T2
PER 11
03903
-03038
0.6552
-0.1790
05567
04370
05624
0.3437
03613
05219
05554
-03520
05334
-0.1020
05
0.0
lojlnj.
05
15000
0.1255
03433
1034501
05101
-0.1633
.03966
1-051941
03251
-03298
-03200
1-031791
-03783
1 0.09361
-03367
1 0.1597 |
03306
0.6070
0.7899
03423
0.1255
13000
03333
03551
-03943
-0.0272
-03253
05676
-03829
-03386
-05118
05107
05
1051 UJ.
03824
1 041481
-03936
1 OXI090~
-03294
1-03318
38
-------
EXHIBIT 6
INT:PER CORRELATIONS
No. Operators Employed
Average Flow
Overloaded
(100%+)
Fully Loaded
(75%- 100%)
Moderately Loaded
(50% - 75%)
Lightly Loaded
(10% -50%)
All
Trickling Filter
PER 1
ฉ
-.15
.02
.06
.16
PER 2
ฉ
0)
.07
-.11
.10
Activated Sludge
PER 1
'M'n'Pfa
ฎ
.12
.01
.04
PER 2
rfK-fiEaM! :
.03
ฉ
-.35
.01
Other
PER 1 1 PER 2
1*0 *fc
.24
<^50)
-.27
-.23
t&Sftr*'
(]69)
.07
-.13
-.03
AD
PER 1
PER 2
Key
I I Strong Correlation
Weak to Moderate Correlation
39
-------
EXHIBIT 7
TA:PER CORRELATIONS
No. Certified Operators
Permit Flow
Overloaded
(100%+)
Fully Loaded
(75% -100%)
Moderately Loaded
(50% - 75%)
Lightly Loaded
(10% -50%)
All
Trickling Filter
PER 1
D n.a.
C .35
B -.02
A -.32
All .09
D -.04
C -.13
B .07
A .02
All -.10
D .08
C -.09
B ;i3
A .20
All .01
D -.23
C -.08
B -.33
A -.25
A1K2T
D .06
C -.01
B -.04
A -.10
A11-.03
PER 2
Q|}
-.i9
-.27
-.14
-.23
-.36
.29
.05
72T
p7o|
7T5
.02
-.03
T7
dD
-.15
-07
(^47)
-.26
-.22
-.20
T24
-.21
-.18
-.15
-.12
7T7
PER 2
ts^taw ;
Ws
C-52)
.08
.25
-34-
.
Ez3
13
-27
^67)
-.31
-.17
-.10
-.09
TTT
-.22
-.06
-.06
-.08
-ToT
All
PER 1
PER 2
Key
I I Strong Correlation
(^__^) Weak to Moderate Correlation
n.a. Not Available
40
-------
correlations) or "other" plants (3 positive correlations). The number
of certified operators at the D level a minimum level does
appear, however, to influence the removal of suspended solids in
trickling filter plants.
In this run, as in subsequent runs, a number of weak to moderate
negative correlations also appeared, suggesting that there appears to
be an inverse relationship between T and PER, rather than a direct
one. This inverse relationship would say that PER is higher in plants
with fewer certified operators per unit of permitted flow. We believe
that this is true, in fact, of certain parts of the sample because of
individual characteristics of the plants in specific size, type,
loading, or location and the ability of their managers, but the
general conclusion that performance can be positively correlated
with the number of certified operators survives because of the
preponderance of positive correlations.
In Exhibit 7 it appears also that the presence of D and C level
operators (4 positive correlations above 0.4 each) correlates with
performance more clearly than the presence of A and B operators (2
and 0 positive correlations, respectively). The use of the ratio of
certified operators to permitted flow (T]A, TIB, and so forth) to
correlate with performance was a first pass at the analysis and
revealed that introducing certification levels in the "T" parameters
tended to improve the frequency of correlations over those found (in
Exhibit 9) using pure staffing data (INT).
Because the ratio of certified operators to permitted flow might not
give the best correlations, however, we looked at two other possible
parameters: Tfi (1B-4B) TC (C1-C4), which were ratios of the
number of certified operators to average yearly plant flow and to
number of operators on the staff (OPL), respectively. In the first
case, the number of operators was divided by average flow to adjust
for any difference in the extent of plant loading in the sample,
largely in the belief that plant hiring practices would probably more
closely match the experienced load (or overload) rather than the
permitted load. In the second case, we were trying to separate the
effect of training certification level from the effect of numbers of
staff. In the TA and TB measures, the operator that is counted is a
trained and certified operator, but he is also an operator who may
already show up in the staffing measures of OPL and INT. Thus, TA
and TB measure the presence of trained and certified operators in
essence, the presence of both training and staff. The TC measure,
however, takes the ratio of trained and certified operators to all
operators, thus proportion of a given staff that is trained.
41
-------
Exhibit 8 shows the results of the TB correlations with PER. In these
data, more significant correlations appear to exist, one negative
correlation disappears, several positive correlations are stronger, and
two negative correlations are weaker than the previous analysis. Plant
performance, therefore, appears to correlate more closely (as judged
by the frequency and magnitude of the correlation index) with the
ratio of trained and certified operators to average plant flow.
Exhibit 9 shows the correlation values using the TC ratios which
were introduced to try to separate the effect of training from the
effect of staffing. This exhibit shows still further improvement over
the earlier date. Correlations in the case of overloaded trickling filter
plants have disappeared, but new and/or much stronger positive
correlations have appeared in the activated sludge and "other"
categories. Because of the greater frequency of correlation, we
calculated and presented on this exhibit the figures for all plants, of
all types and sizes. The relative frequency of correlation of the TA,
TB, and TC ratios with performance is shown in Exhibit 10.
The TC measure an indicator of the proportion of the staff of a
plant that has been exposed to training is the best determinant of
performance that we have found. Where performance is high, the
training level of the staff is the most likely reason. Although
successful plant operation correlates to some degree with size of
staff, it seems to be much more directly related to training achieved.
If training is the major reason for sustaining good performance, the
performance of plants that improve should be explainable in terms of
training as well. Section A, above, presents a case-by-case view of
how training can improve plant performance. To test quantitatively
the hypothesis that training relates to performance improvement, we
divided our sample of 124 plants into three groups:
(i) Those plants whose performance on BOD or sus-
pended solids removal declined by 10 percent or
more in 1971, as measured by a comparison of
performance figures for the first three months and
the last three months of 1971.
(ii) Those plants whose performance stayed roughly the
same (that is, within +10 percent during 1971, as
measured above).
42
-------
EXHIBITS
TfirPER CORRELATIONS
No. Certified Operators
Average Flow
Overloaded
(100%+)
Fully Loaded
(75% -100%)
Moderately Loaded
(50% - 75%)
Lightly Loaded
(10% -50%)
All
Trickling Filter
PER i
D n.a.
C (AT)
B In
A -.33
All -.16
D -.03
C -.10
B .14
A .05
All -.03
D .08
C -.01
B .19
A .20
All .11
D -.23
C -.06
B -.14
A -.21
All -.11
D .05
C .05
B .04
A -.03
All .06
PER 2
cfb
^58
-.25
-.07
-.20
-.33
.35
.08
-.19
@
.19
.06
-.03
.33
(!52)
-.08
11
t46)
-.03
Cli)
.13
.02
-.17
.14
Activated Sludge
PER 1
ซft*Sw
dP
.17
,2&
G4U
n.a.
-.20
HA
Q>
-jf
(csSOj)
oS>
.09
.30
-.14
.37
.36
PER 2
'
J&CTttfr
-28
tzil
n.a.
-.26
-71
CscD
-.10
n.a.
.20
-.31
-.18
.07
.08
.34
-.27
.13
.31
Other
PER 1
Hfe F*w
n.a.
.17
-.33
.26
.34
-.02
-.36
-.24
-.20
(^43)
-.30
-.23
-.22
-.22
-.23
-.17
-.14
-.13
-.12
-.13
PER 2
fKl&fo
ija.
Qt>
.08
.25
.36
,7
[OTO)
.OS
-.26
C!E>
-.22
-.17
-.14
-.14
-.16
-.15
-.11
-.10
-.10
-.10
All
PER 1
PER 2
Key
Strong Correlation
Weak to Moderate Correlation
n.a. Not Available -
43
-------
EXHIBIT 9
Tc:PER CORRELATIONS
No. Certified Operators
No. Operators Employed
Trickling Filter
PERI
TERT
Activated Sludge
TERT
wfr
PER
Other
All
PER 2
PER 1
PER 2
Overloaded
(100%+)
n.a.
.01
,27
,30
-.27
Fully Loaded
(75%-100%)
D .11
C .14
B .18
A .29
All .26
n.a.
.07
.14
.26
.10
Moderately Loaded
(50%-75%)
D .07
C ,01
B .07
A .16
All .03
n.a.
,28
,27
,35
,34
Lightly Loaded
(10%-50%)
D -.23
C .10
B -.01
A ,29
All .01
-.30
.20
.33
.24
.26
All
D .04
C .03
B -.02
A ,12
All .00
.09
.33
-.24
.34
^32
,15
-.07
.08
^06
,01
.05
.08
-.07
.25
.06
.24
.30
.08
,00
.28
Key
I j Strong Correlation
(^^) Weak to Moderate Correlation
n.a. Not Available
44
-------
EXHIBIT 10
RELATIVE CORRELATION FREQUENCIES BETWEEN
TA, Tfi, and TC FACTORS WITH PERFORMANCE
Positive Correlations
Strong
Moderate
Negative Correlations
Strong
Moderate
Total
TA:PER
Exhibit 7
14
3
11
6
0
6
20
Tfi:PER
Exhibit 8
17
5
12
4
0
4
21
TcC:*PER
Exhibit 9
27
10
17
4
0
4
31
*Without consideration of "all types" column in Exhibit 9.
45
-------
(iii) Those plants whose performance improved by 10
percent or more in BOD or suspended solids removal
in 1971 as measured above.
For each of the three groups, we then computed mean figures for TB
values first and the training index of TIND and produced the results
shown in Exhibit 11. Exhibit 11 shows that the plants that made a
10 percent or better improvement in performance in 1971 had, on
the average, significantly higher values of TB and a significantly
higher training index than plants which stayed the same or achieved
worse performance. (We have been unable to satisfactorily explain
why those plants that stayed the same, in many cases, have lower T
values than those whose performance degraded.) Exhibit 12 shows
the relative values of these correlations using the "worse" cases as the
standard. In every training measure, the "better" case has higher
training parameters, ranging from 1.3 to 40.0 times as high as the
worse case, whereas in no case is the effect of staffing (INT) as
important.
C. Conclusions Regarding the Impact of Operator Training on
Plant Performance
Examinations of case studies of plants involved in Operation
Cleansweep and plants cited by WQB district supervisors as having
experienced training benefits provided strong indications that train-
ing has had a strong beneficial influence in improving plant
performance in a significant proportion of plants whose performance
has been historically substandard. In addition, the potential for
training benefits in plants encumbered by inadequate facilities is
great and may be expected to be realized when physical obstacles are
removed.
A computer correlation study of a sample of Texas wastewater
treatment plants, conducted independently of the earlier two studies,
showed that the proportion of the staff of a plant that has been
exposed to training is the best determinant of performance, both for
plants with sustained records of good performance and for plants
that made a 10 percent or better improvement in performance in
1971.
As a result of these separate studies, we may conclude that training
bears a direct and measurable relationship to plant performance
improvement as well as to plant performance levels. Both of these
relationships could have been explored further with greater data
availability (on all plants in Texas) and additional study resources. It
46
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EXHIBIT 11
CHANGES IN PLANT PERFORMANCE WITH
TRAINING AND STAFFING PARAMETERS
Parameter
TlB(D)
T2B(C)
T3B(B)
T4B(A)
TB(A11)
INT
TIND
BOD
Worse
.0006
.0150
.0120
.00008
.02768
.0081
6.186
Same
.0003
.0140
.0062
.0005
.0210
.0101
5.160
Better
.0011
.0400
.0200
.0032
.0643
.0109
10.043
TSS
Worse
.0009
.0200
.0100
.0010
.0319
.0134
6.858
Same
.0001
.0085
.0072
.0005
.0163
.0081
6.606
Better
.0012
.0520
.0270
.0038
.0830
.0076
10.950
-------
EXHIBIT 12
RELATIVE VALUES OF
CORRELATIONS OF CHANGES EM PLANT PERFORMANCE
WITH TRAINING AND STAFFING PARAMETERS
00
Parameter
TlB(D)
T2B(C)
T3B(B)
T4B(A)
TB(All)
INT
TIND
BOD
Worse
1.0
1.0
1.0
1.0
1.0
1.0
1.0
Same
0.5
0.9
0.5
6.2
0.7
1.3
0.8
Better
1.8
2.7
1.7
40.0
2.3
1.3
1.6
TSS
Worse
1.0
1.0
1.0
1.0
1.0
1.0
1.0
Same
0.1
0.4
0.7
0.5
" 0.5
0.6
1.0
Better
1.3
2.6
2.7
3.8
2.6
0.6
1.6
-------
the plant was brought before the WQB, the operator was an
uncertified part-time employee. Operator training recommended by
the Board was under way at the close of 1971, but the results of
training had not yet materialized at the time this report was written.
The WQB expects good performance from this plant in 1972.
Case 11
At the beginning of 1971, this plant was seriously noncompliant on
BOD and TSS and was not self reporting. During 1971, the hiring of
a trained and certified operator has caused dramatic improvement in
both performance areas, although the plant is not yet compliant on
TSS.
Case 12
The Case 12 facility was an older plant, in deteriorated condition,
that was noncompliant on BOD and TSS. During 1971, some repairs
were made, and the town initiated action to acquire a new plant. The
potential for training impact after addition of new facilities is strong.
Case 13
This town has three small plants, all of which are seriously
overloaded and seriously noncompliant on BOD and TSS. Subse-
quent to the WQB hearing, the town decided to join a regional plant
now in the planning stage. Training does not appear to have a bearing
on the problem or its resolution in this case.
Case 14
The plant in Case 14 was seriously overloaded and noncompliant on
BOD and TSS in large part because of a sewer collection system
that was permitting excessive infiltration. During the year since the
Board hearing, the country has hired a consulting engineer to survey
the situation. On the basis of this work, improvement has been
noticed on both BOD and TSS. Training does not have a bearing on
this problem; however, a properly trained and experienced operator
might have been able to bring about significant improvement in lieu
of calling in a consulting'engineer.
Case 15
This plant needed additional treatment facilities, including chlorina-
tion capability, and it was not reporting complete information on its
15
-------
self-monitoring reports. Because of its failure to respond to the
WQB's inquiries, this plant has been referred to the State Attor-
ney General's office for action. It should be noted that the
WQB, through corrective proposals, makes an extended effort
to avoid such fines. Further, only in instances of complete un-
cooperativeness are these matters referred to the State Attorney
General's office. The potential for training impact after the
addition of new facilities is strong.
Case 16
This overloaded plant was noncompliant on BOD and TSS and
was not sufficiently chlorinating its effluent. Improvement has
been effected in chlorine content of effluent and on TSS, but not
in BOD performance. Training does not appear to have an in-
fluence here.
c. Findings from the Operation Cleansweep Investi-
gation. The types of problems, solutions selected, and apparent
influence of training in resolving the 16 cases of noncompliance
with WQB standards, as described above, are summarized in
Exhibit 1. As shown, the performance of four of the plants that
were in serious violation of their state wastewater permits in
early 1971or 25 percent of the plants brought before the
WQB in the first quarter of 1971was improved significantly
at least in part through operator training. Two of these plants
became compliant on both BOD and TSS*measures. The plants
that appeared most responsive to the influence of training were
those characterized by poor operation as a result of lack of
operator knowledge, rather than those that were seriously over-
loaded.
In addition to the cases identified as responding positively to
training, there was one casecase 10in which surveillance
authorities observed that the operator was just undergoing
training at the time of this report and anticipated the training to
yield strong positive results. At least two other problem situa-
tionscases 5 and 14, in which consulting engineers were re-
tainedmight have been resolved through the hiring of a
properly trained operator.
Thus, from this sample of "problem plants" in serious violation
of pollution control standards, possibly as many as 45 percent
(seven out of 16) exhibited problems potentially susceptible to
resolution through operator training, and 25 percent (four out
of 16) effectively used training in resolving those problems.
2. WQB District Supervisors' Survey
a. Overview. The survey of the WQB district super-
visors to determine which plants had noticeably benefited from
training began as a telephone interview with each of the 12 district
16
-------
would have been useful, for instance, to vary the rate of performance
improvement to determine the precise relationship between training
and performance.
49
-------
PARTY
THE RETURN ON THE PUBLIC INVESTMENT IN
WASTEWATER TREATMENT PLANT OPERATOR TRAINING
Part IV of this report concluded that training of wastewater
treatment plant operators does have several beneficial effects upon
the quality of plant effluent and efficiency of plant maintenance and
operations. The formulation of a statement of the precise dollar
value of these benefits would be very difficult, if not impossible, and
it is not within the scope of this study to attempt to produce such a
statement. However, it is possible from the study to develop some
quantitative insights into the value of training benefits that should be
useful to decision-makers considering the desirability of sponsoring
and/or conducting additional operator training.
The public investment required to initiate and support the effective
operation of a municipal wastewater treatment plant is substantial
estimated in excess of $160 million in Texas. This investment is
made with the expectations that capital plant will be utilized in such
a way as to maximize the useful life and that specified levels of
effluent quality will be achieved. Therefore, this part of the report
considers the value to the public of training benefits in terms of:
(i) The value of the capital assets entrusted to the care of
individual operators.
(ii) The investment that is wasted when a treatment plant
does not fulfill its BOD and TSS removal
requirements.
A. Value of Capital Assets per Operator
The value of the capital assets entrusted to individual Texas
municipal wastewater treatment plant operators was estimated by
calculating the operator population and capital investment for a
random sample of plants in the state of Texas. In most aspects of the
calculations, supplementary data were acquired with the cooperation
of the Texas WQB.
1. Explanation of Calculations
To determine the average value of capital assets per operator
represented by Texas municipal wastewater treatment plants, using a
Kendall and Smith Table of Random Numbers, a random sample of
51
-------
50 plants was selected from the EPA STORET information system,
which lists 993 separate municipal treatment plants in Texas. These
50 selected plants are identified in Column 1 of Exhibit 13:
Each of these 50 plants was then categorized by physical characteris-
tics according to nine basic types of conventional wastewater
treatment plants listed in the study, "Estimating Costs and Man-
power Requirements for Conventional Wastewater Treatment
Facilities," prepared by Black and Veatch, Consulting Engineers, for
EPA in October 1971. When a random STORET sample plant
indicated a nonconventional plant type that is, one that did not
correspond to the Black and Veatch categories the plant was
discarded from consideration and another random sample substi-
tuted. The nine plant types, coded as numbers 1 through 9 in
Column 2 of Exhibit 13, are as indicated in Exhibit 14. Plants below
.5 MGD design flow are indicated by an asterisk in this column.
Next the design size for each sample plant was extracted from the
STORET data and rounded to the nearest of 1, 3, 5, 10, 20, 35, 65,
80, or 100 million gallons per day in order to gain compatibility with
the plant-size categories established in the Black and Veatch study.
Plant design capacities as rounded for the 50 randomly selected
plants are shown in Column 3 of Exhibit 13.
The operator complement for each sample plant Exhibit 13,
Column 4 was determined on the basis of the Black and Veatch
study, which sets forth standard plant manning tables for estimated
staffing needs developed in that study for operators (and other plant
personnel) according to plant type (nine categories) and design
capacity. While actual staffing in a given plant may not meet these
estimated needs, this study presents the best available basis for
determining complement. Because many operating plants are widely
reported to be staffed below recommended levels, it is likely that our
staffing estimates understate capital investment.
Further, we suspect that the Black and Veatch data overstate
operators because they lack discretion for plants below the design
flow of 1.0 MGD. Over 60 percent of the random samples were
plants with design flow of less than .5 MGD. Such plants are likely to
have one or two operators, often part-time. While the Black and
Veatch minimum for its 1 MGD category is four operators for
primary plants and five for secondary, field research indicates that
the new smaller plants are often self contained and automatically
controlled requiring little attention and that the older plants,
though needing additional workers to become effective, do not have
52
-------
EXHIBIT 13
CALCULATED CAPITAL INVESTMENT PER OPERATOR
FOR SO RANDOMLY SELECTED PLANTS
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
IS.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
(1)
Plant Name
Seabrook
Itasca
Stamford
Chile
Lewisville
Monahans
Alpine
Mineral Wells
Universal City
Bellville
Lackland City
Galveston County No. I
El Paso (Ascarate)
Houston WCID No. 44- Plant
No. 2
Bexar County (Kiiby)
Columbus
Sour Lake
Houston Chadwick Manor
Granger
Waxahachie
Byers
Midland
Bexar County (Oak Hills)
Houston WCID No. 78 (Alief)
Sinton
(2)
Type
4
1
4
7
4
4
1
4
7
4
4
4
4
4
7
4
7
4
4
4
7
4
7
4
4
<3)
Sin
1
ซ
*
1
1
*
1
1
*
*
1
*
*
*
1
*
1
1
5
*
ป
1
<ซ>
Number of
Opinion
5
1
1
1
5
5
1
5
5
1
1
5
1
1
1
5
1
1
5
5
1
7
1
1
S
(5)
Population
Served
5,000
1,200
5,400
8,000
3,300
11,000
5,400
33,000
15,000
2,000
6300
5,300
2,500
4,700
2,300
3,500
1,600
500
1,300
11,800
500
61,700
6,300
2,000
4,800
(ซ)
Estimated Capital
Investment (ECI)
S 150,000
54,000
163,200
200,000
115,500
220,000
162,000
528,000
300,000
90,000
189,000
159,000
112,500
164.500
103,500
122,500
72,000
57,500
58,500
236.000
57,500
678,700
189,000
90,000
168.000
(7)
ECI per
Operator
S 30,000
54,000
163,000
200,000
23,100
44.000
162,000
10,560
60,000
90,000
189,000
31,800
112,500
164,500
103,500
122,500
72,000
57,500
11,700
47.200
57.500
96,957
189,000
90.000
33.600
"Under .5 MOD.
53
-------
EXHIBIT 13 (Cont'd)
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
(1)
PbmtName
Silverton (Plaza Lake)
Eastland
Graham
Post
Van
Beeville (New Plant)
Port Arthur (El Vista WCID No. 1 1 1 )
Colorado City
Fort Bend County (Stafford)
Humble
Kemp
Kemah
Pasadena (North Side)
Alia Loma (WCID No. 8)
Arp
Lorenzo
Sugarland (Quarters Plan)
Lancaster
Graver (Farwell Draw)
San Diego (Stp Outfall 1)
Pinehurst
Wortham (Northeast)
EUchart
El Campo (Plant No. 1 )
Mabank
TOTAL
(2)
Type
1
4
4
1
4
4
4
4
7
4
4
4
4
4
4
1
4
4
I
4
7
1
4
4
1
(3)
Size
*
1
*
1
*
1
*
*
1
*
5
*
*
*
ซ
*
1
*
1
*
(4)
Number of
Operators
1
1
5
1
1
5
1
5
I
1
5
1
7
1
1
1
1
1
1
1
5
1
1
5
1
126
(S)
Population
Served
1,050
3,000
9,400
4,430
1,700
6.000
1,200
6,700
3,000
1,700
950
3,000
225,000
1,400
700
1,300
700
5,500
1,000
3,000
1,800
1,100
1,000
8,760
1,150
(6)
Estimated Capital
Investment (ECI)
47,250
105.000
235,000
155.050
76,500
180,000
54,000
201.000
105,000
76,500
80,750
105,000
1,125.000
63,000
59,500
58,500
59,500
165,000
85,000
105.000
81.000
49,500
85,000
219,000
51,750
S8.068.200
(7)
ECI PER
Operator
47.250
105,000
47,000
155,050
76,500
36,000
54,000
40,200
105,000
76,500
16,150
105,000
160,714
63,000
59,500
58,500
59,500
165,000
85,000
105,000
16,200
49,500
85,000
43,800
51,700
$ 64,033
"Under .5 MGD.
54
-------
l/l
I/I
EXHIBIT 14
SUMMARY OF BLACK AND
VEATCH PLANT TYPE CATEGORIES
Type
1
2
3
4
5
6
7
8
9
Liquid Treatment
Primary
X
X
X
X
X
X
X
X
X
Trickling
Filter
X
X
X
Activated
Sludge
X
X
X
Sludge Handling Facilities
Digestion
and Beds
or Lagoons
X
X
X
Digestion
and Sludge
Dewatering
X
X
X
Dewatering
and
Incineration
X
X
X
-------
sufficient staff. Accordingly, for all sample plants of a design
capacity under .5 MGD, we have imputed a complement of one
operator.
Estimated capital investment per plant (Column 6 of Exhibit 13) was
calculated on the basis of population served by each plant and Texas
cost data developed under the Construction Grants Program (Public
Law 660) for fiscal year 1969. Population served by each sample
plant (Column 5) was derived from STORET system information in
most cases. Investment costs were derived from the graph shown in
Exhibit 15, which charts population served against per capita
investment costs experienced under the Construction Grants Program
for secondary treatment plants, excluding land costs. Estimated
capital investment per plant (Column 6) was calculated by multiply-
ing the Column 5 population data by the per capita cost of
investment derived from Exhibit 15. Because our random sample
includes a few primary plants, capital investment estimates for those
plants may be slightly overstated.
The estimated capital investment (ECI) for each plant (Column 6 of
Exhibit 13) was divided by the calculated number of operators
(Column 4) to derive the estimated capital investment per operator
(Column 7) for each of the 50 randomly selected plants.
Overall, in the 50-plant sample, there was a total estimated capital
investment of $8,068,200 under the responsibility of an estimated
126 operators, for an ECI per operator of $64,033. This investment
per operator is substantially higher than the $10,200 invested by
American industry for each of its production workers.
2. Interpretation of Calculations
These conservative figures reveal the minimum extent to which
public investment in wastewater treatment facilities is exposed to
risk when plant operation and maintenance is entrusted to an
untrained or inadequately trained operator. The real extent of the
risk accepted may be better appreciated when it is understood that
the ECI per operator offered above is calculated on the theory that
all operators are working at the same time (that is, that all of the
plants in the sample conduct single-shift operations). Although no
data are available to indicate the dispersion of operators among
shifts, common sense and casual observation are sufficient to
conclude that some plants have operators on two or even three shifts.
If the calculation were made on the basis that to run two shifts
necessitated an even split of operators between shifts, the average
value of plant entrusted to each operator at any one time would be
56
-------
EXHIBIT 15
PER CAPITA WASTEWATER TREATMENT PLANT
INVESTMENT COST DATA
80
75
70
65
60
55
501
n
o
g 45
w
O
ซ 40
30
25
20 J
15
10
5
0
. o n. r>
10 20 30 40 50 60 70 80 90 100 UO 120
Sewage Treatment Plant Cost per Capita, dollars
Source: "Regional Sewerage Systems and Treatment Costs in
Texas," Nicholas W. Classen, Bobby G. Scalf, and Joseph
B. Copeland, Jr., Texas Water Quality Board, Austin,
Texas, Agency Publication No. 70-03.
57
-------
closer to $ 128,000. Further, as explained above, the use of Black and
Veatch recommended staffing levels for this calculation renders the
number of operators somewhat high, thus resulting in a substantial
understatement of the average investment per operator.
Perhaps more important than the average is that many operators in
Texas and presumably elsewhere are daily entrusted with as
much as $200,000 worth of plant and some with even more. In
analogy, few drivers would entrust a $3,000 automobile to an
untrained, inadequately trained, or unlicensed driver, and a waste-
water treatment plant operator is daily responsible for over 20 times
this investment.
In contrast to the ECI per operator, which may well range in excess
of the $64,033 presented in Exhibit 13, EPA experience in the
Public Services Careers Program and other similar operator training
programs suggests that the cost of training a single operator,
exclusive of support costs associated with training of the disadvan-
taged, average in the vicinity of $565.
B. Wasted Investment Through Substandard Effluent
Another perspective on the value of training benefits was developed
through further consideration of some of the plants which were
subjects of the Part IV case studies to determine the extent to which
training prevented waste of capital investment that would have been
caused by delivery of a substandard product. In a number of the case
studies, plants were identified in which recent training could be
isolated as the substantial cause of improved performance. For
certain of these improvement cases, quantitative data showing the
quality of the effluent in terms of BOD and TSS before and after
training were available through the Texas Water Quality Board. These
data were manipulated as described below to calculate the "stop-
loss" on capital investment. A further calculation offset the cost of
training against the stop-loss on capital to estimate the net return on
the training investment for these plants.
1. Explanation of Calculations
The plants selected for inclusion in this portion of the study include
the four plants cited in Operation Cleansweep in the first quarter of
1971 for noncompliance with WQB standards that could be
identified as achieving performance improvement largely as a result
of training. In addition, 15 plants identified by the Texas WQB
district supervisors as having improved their performance as a result
58
-------
of training since 1970 were included because data were available. For
all 19 of these case study plants, data to substantiate the perfor-
mance improvement were derived from the Texas Water Quality
Board self-reporting information system. Data on the 19 plants are
presented in Exhibit 16.
Effective improvement in performance (Column 2) was calculated on
an average basis, giving equal weight to BOD and TSS levels. The
figures presented in Column 2 of Exhibit 16 were derived by
calculating the difference between first-quarter and last-quarter 1971
levels of BOD and TSS and averaging them.
Column 3 sets forth an average of the BOD and TSS performance
standards established for each plant by the Texas Water Quality
Board.
The capital investment figures presented for each plant in Column 4
were calculated on the basis of population served by each plant and
Texas cost data developed under the Construction Grants Program
for fiscal year 1969, as described in the calculation of ECI per
operator in Section A-l above. Supporting data are provided in
Appendix A.
The effectiveness with which the capital investment for each of these
plants was being utilized before and after training was expressed in
terms of the imputed proportion of the investment that was actively
producing to design capacity. Pre-training effective capital was
calculated by dividing the standard for each plant by the average
combined BOD/TSS performance before training (in the first quarter
of 1971); the quotient, representing the fraction of intended
BOD/TSS removal being realized before training, was multiplied by
the plant's total capital investment to determine the equivalent fully
effective capital investment that would produce the same quality
effluent. In some instances, plants that were performing well within
their compliance specifications have pre-training effective capital
estimates well in excess of their actual capital investment costs. This
implies that the plants were already performing more effectively than
was hoped.
Post-training effective capital was calculated by dividing the standard
for each plant by its average combined BOD/TSS performance after
training (in the last quarter of 1971); the quotient representing the
fraction of plant effectiveness after training was again multiplied by
the total capital investment in the plant to determine the equivalent
effective capital represented by its performance. Pre-training and
59
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EXHIBIT 16
CALCULATION OF "STOP-LOSS" ON CAPITAL INVESTMENT
AND RETURN ON TRAINING INVESTMENT IN 19 CASE STUDIES
(I)
Plant
Kaufman
Corpus Christ! (WSIde)
Corpus Christi (B'Way)
Mathis
Lockhart
Jasper
ป Beaumont
Brownwood
Midland
Odessa (BOD only)
Grandview
Forney
Piano
Nocona
Bridgeport
Gainesville
Brownsville
Donna
Edirftmrg
TOTAL
AVERAGE
(2)
Average
Effective
Change
38.5
14.0
3,8
23.2
9.5
4.6
5.9
30.5
5.9
178.8
6.5
10.2
4.0
32.0
16.0
6.7
12.7
25.2
4.4
(3)
Avenge
BOD/TSS
Standard
34.5
20.0
20.0
57.0
20.0
103.0
20.0
23.0
20.0
35.0
20.0
20.0
20.0
77.0
30.0
20.0
20.0
20.0
20.0
(4)
Capital
Investment
164,500
175,000
400,000
174,000
207,000
150,000
544,000
342,000
678,700
795,300
85,000
78,750
260,000
153,125
140,000
300,000
643,000
198,000
360,000
5,848,375
307,809
(5)
Pre-Trainlng
Effective
Capital
85,540
98,000
240,000
140,940
298,080
364,500
451,520
430,920
1,174,151
508,992
115,600
96,075
239,200
208,250
128,200
232,500
482,400
39,600
288,000
5,622,468
295,919
(6)
Post-Training
Effective
Capital
205,625
164,500
272,000
210,540
910,800
408,000
598,400
639,540
2,395,811
1,725,801
207,400
255,938
293,800
482,343
257,600
312,000
926,208
87,120
348,480
10.701,906
563,258
(7)
Stop-Lois
on Capital
120,085
55,500
32,000
69,600
612,720
43,500
146,880
208,620
1,221,660
1,216,809
91,800
159,863
54,600
174,093
129,400
79,500
443,808
47,520
60,480
4,968,438
261,497
(8)
Costal
Training
2,825
3,955
4,520
2,825
2,825
3,390
3,390
2,825
3,955
5,085
565
565
3,955
565
565
2,825
3,955
2,825
2,825
53.675
2,825
(ป)
Net
Return
117,260
62,545
27,480
66,775
609,895
40,110
143,490
205,795
1,217,705
1,211,724
91.235
159,298
50,645
173,528
128,835
76,675
439,853
44,695
57,655
4,926,763
259,303
(10)
Ratio of
Training
Investment:
Net Return
1:42
1:15
1:6
1:24
1:216
1:12
1:42
1:73
1:307
1:238
1:161
1:282
1:13
1:307
1:228
1:27
1:111
1:16
1:20
1:91
00
%
Improvement
After
Training
240
166
112
149
316
112
132
148
204
334
178
266
122
231
198
135
191
155
121
(12)
%
Reduction of
BOD/TSS
in Effluent
58
40
11
65
68
11
24
32
51
65
44
62
18
57
49
26
48
36
17
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post-training effective capital estimates appear in Columns 5 and 6,
respectively, of Exhibit 16. "Stop-loss" on capital (Column 7) was
derived by subtracting Column 5 from Column 6.
The number of operators in each plant was estimated according to
Black and Veatch staffing guides and EPA STORET data regarding
type and size of plants, as described in section A-l, above. Since the
actual proportion of the operator staff trained in each case was
unknown, it was assumed that all operators in each plant were
trained; clearly this method overstates the number of trained
operators. The number of operators for each plant was then
multiplied by $565, the cumulative historic cost experience of EPA
in administering the Public Service Careers Program for operator
training (exclusive of the expense of supportive services offered to
disadvantaged trainees). Resulting training cost calculations are
shown in Column 8.
Net gain in effective capital, shown in Column 9, was derived by
subtracting Column 7 from Column 8. The Column 10 ratio of
training investment to net capital return was calculated by dividing
Column 9 by Column 8.
Percentage improvement in plant performance in terms of increase in
BOD and TSS removal was determined by dividing BOD/TSS
combined average performance in the first quarter of 1971 by the
level of performance achieved after training, in the last quarter of
1971. The results of this procedure are presented in Column 11 of
Exhibit 16.
Finally, the percentage of the reduction of BOD/TSS in the effluent
of each of these plants was determined by dividing the effective
change (Column 2) by the BOD/TSS performance achieved before
training (in the first quarter of 1971).
2. Interpretation of Calculations
As shown in Exhibit 16, the net improvement in effective capital in
the 19 case-study plants was equivalent to a combined investment of
$4,926,763. For every dollar invested in training in these plants, the
equivalent of an additional $91 investment was activated in terms of
improved performance. As a result of training, the quality of effluent
produced by all of these plants improved substantially, in a range
from 11 to 68 percent reduction of average combined BOD/TSS.
Further, overall improvement ranged between 112 and 334 percent
over pre-training levels.
61
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These results are sufficiently startling to warrant further comment, in
terms of both the reliability of the calculations and their implica-
tions.
It is recognized that the data utilized to produce the calculations
displayed in Exhibit 16 are less than perfect and could have been
improved substantially upon additional research conducted over a
longer period and with more resources than were available for this
study. In addition, the availability of additional data would have
permitted refinement of the calculation methodology and might have
permitted consideration of operation and maintenance costs. The
limited qualitative data we have indicates that both operation and
maintenance costs are likely to rise after training because trained
operators command higher wages and are likely to perform vital
routine maintenance tasks that were previously ignored. Further,
consideration might well have been given to the value of the possible
extended plant life that could result from improved operator
maintenance procedures as a result of training.
A further qualification is found in the methodology. The final
calculations represent a measure of stop-loss on capital and return on
training investment over the life of plants only if it is assumed that
the plants had always, before training, been operating at the level of
effectiveness measured just prior to training (during the first quarter
of 1971) and that they will continue, after training, to perform at
least as well as the level achieved just before training (in the last
quarter of 1971). Obviously performance in the past and future may
vary with a variety of independent phenomena, such as quantity and
quality of influent, plant age, and so forth.
Nevertheless, we believe that the calculations presented in Exhibit 16
do offer a reasonable benchmark of the value that can be attributed
to investment in wastewater treatment plant operator training. If
these figures overstate the value of training investment by as much as
50 percent, the conclusion that the payoff an operator training
investment is enormous remains valid.
On the basis of this study, it is not possible to state with certainty
that the training investment results that are presented in this report
may be imputed to operator training in general throughout the state
of Texas and throughout the country. The fact that in 12 of the 16
plants called before Operation Cleansweep in the first quarter of
1971, training had no apparent influence on subsequent performance
improvement does not say that trained operators were not essential
to effective operation in those plants. It does say that without regard
62
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to the status of operator training in those plants, other adjust-
ments in plant, equipment, staffing, or funding were necessary
before improved operating efficiency would be possible. We can
accept as fact that in many plantsand probably most plants
training acts in combination with other factors to cause effective
performance. Yet the fact that a number of cases were found in
Texas in which training could be identified as the only significant
variable leading to effective performance signifies that training is
by itself, as well as in combination with other factors, critical to
realization of anticipated return on capital investment.
Thus far, we have been examining overall return on training
investment without reference to the different views of investment
and return as they might appear at different levels of the govern-
ment. Typically the largest share of the capital for investment in a
treatment plant comes from the federal and state governments.
On the other hand, local governments bear almost the entire
operation and maintenance costs. If, as we suspect, the cost of
operation and routine maintenance goes up with training, local
decision-makers might see a negative incentive to invest in train-
ing. This might be true particularly if the local government
must pay for all or part of the training.
However, in Texas, as in some other states, there is a very real
potential out-of-pocket cost to the local government if its plant
effluent is not meeting the state standard. This is a daily fine to be
paid to the state for noncompliance; in Texas, it is $1,000 a day
for each day of noncompliance. These fines are imposed only
after exhaustive efforts have been made by the WQB, and where
there is utter disregard for the Board's recommendations. While
plant effectiveness varies and generally noncompliant plants
may be in compliance on some days, the fine can obviously add
up rapidly and become a very substantial sum. Particularly for
smaller communities, such a fine would seem to provide an
incentive for communities to train operators if this is the action
required to reach compliance.
In 17 of our sample cases in Part IV, plants moved from a gen-
erally noncompliant to a compliant status substantially as a result
of operator training. Bringing a plant into compliance represents
a very real return on training investment in the fear of fines
avoided for these localities. However, because the fine is a pay-
ment from one government body to anothera transfer of
money from one jurisdiction to another encompassing jurisdic-
tionit is not a real saving to the national or even statewide
public. Therefore, we have not calculated this as a part of the
national return on training.
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C. Conclusions Regarding the Return on the Public Investment in
Wastewater Treatment Plant Operator Training
The average estimated capital investment per operator is at least
$63,700 and could well be closer to $127,400. Further, many
individual operators in Texas and presumably elsewhere daily
hold responsibility for capital plant valued at $200,000 or more. All
of these figures are considerably higher than the $10,200 invested on
the average by American industry for each of its production workers
and support the need for training as insurance that capital will be
used optimally.
An analysis of 19 of the case-study plants discussed in Part IV of this
report revealed that for every dollar invested in training, the
equivalent of an additional $91 investment in capital plant was
activated in terms of improved performance. Further, the degrees of
reduction of BOD/TSS in plant effluent and levels of overall
improvement following training indicate conclusively that for these
plants, the value of the return on training was high hi terms of both
dollar investment and cleanliness of water treated.
64
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APPENDIX A
ECI PER OPERATOR CALCULATIONS FOR 19 CASE STUDIES
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
0)
PbntName
Kaufman
Corpus Christi(WSide)
Corpus Christi (B'Way)
Mathis
Lockhart
Jasper
Beaumont
Brownwood
Midland
Odessa
Grand view
Forney
Piano
Nocona (South)
Bridgeport
Gainesville
Brownsville
Donna
Edinburg
O)
TVpe
4
4
5
4
4
1
4
4
4
7
7
4
4
7
1
4
4
4
4
(3)
Size
1
3
10
1
1
3
3
1
5
5
*
*
5
*
*
1
5
1
1
(4)
Number of
Operators
5
7
8
5
5
6
6
5
7
9
1
1
7
1
1
5
7
5
5
(5)
Population
Served
4,700
5,000
82,000
5,800
6,900
5,000
34,000
18,000
61,700
72,300
1,000
1,750
13,000
4,375
3,000
15,000
53,600
6,600
20,000
0ป
Estimated Capital
Investment (ECI)
164,500
175,000
400,000
174,000
207,000
150,000
544,000
342,000
678,700
795,300
85,000
78,750
260,000
153,125
140,000
300,000
643,200
198,000
360,000
(7)
ECI
Per Operator
32,900
25,000
50,000
34,800
41,400
25,000
90,666
68,400
96,957
88,367
85,000
78,750
37,142
153,125
140,000
60,000
91,886
39,600
72,000
Under .5 MGD
65
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ACKNOWLEDGMENTS
Harbridge House wishes to acknowledge the assistance of the Texas
Water Quality Board (WQB) in permitting this investigation to be
made and materially assisting in its execution. The WQB generously
provided most of the data on the case examples and the statistical
studies from their extensive and well-organized files and reports. Also
to be thanked is the Water Resources section of the North Central
Texas Council of Governments (NCTCOG) whose personnel
materially helped in data collection and served as a sounding board
for some of our findings.
Despite the generous assistance of these two organizations, the
findings, conclusions, and recommendations presented in this report
remain the responsibility of Harbridge House.
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